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Pound, Michael P., Atkinson, Jonathan A., Townsend, Alexandra J., Wilson, Michael H., Griffiths, Marcus, Jackson, Aaron S., Bulat, Adrian, Tzimiropoulos, Georgios, Wells, Darren M., Murchie, Erik H., Pridmore, Tony P. and French, Andrew P. (2017) Deep machine learning provides state-of-the-art performance in image-based plant phenotyping. GigaScience, 6 (10). pp. 1-10. ISSN 2047-217X

Morris, Emily C., Griffiths, Marcus, Golebiowska, Agata, Mairhofer, Stefan, Burr-Hersey, Jasmine, Goh, Tatsuaki, von Wangenheim, Daniel, Atkinson, Brian, Sturrock, Craig J., Lynch, Jonathan P., Vissenberg, Kris, Ritz, Karl, Wells, Darren M., Mooney, Sacha J. and Bennett, Malcolm J. (2017) Shaping 3D root system architecture. Current Biology, 27 (17). R919-R930. ISSN 1879-0445

Atkinson, Jonathan A., Lobet, Guillaume, Noll, Manuel, Meyer, Patrick E., Griffiths, Marcus and Wells, Darren M. (2017) Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies. GigaScience, 6 (10). pp. 1-7. ISSN 2047-217X

Postma, Johannes A., Kuppe, Christian, Owen, Markus R., Mellor, Nathan L., Griffiths, Marcus, Bennett, Malcolm J., Lynch, Jonathan P. and Watt, Michelle (2017) OpenSimRoot: widening the scope and application of root architectural models. New Phytologist, 215 (3). pp. 1274-1286. ISSN 1469-8137

Atkinson, Jonathan A., Wingen, Luzie U., Griffiths, Marcus, Pound, Michael P., Gaju, Oorbessy, Foulkes, John, Le Gouis, Jacques, Griffiths, Simon, Bennett, Malcolm J., King, Julie and Wells, Darren M. (2015) Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat. Journal of Experimental Botany, 66 (8). pp. 2283-2292. ISSN 1460-2431

Thesis (University of Nottingham only)

Griffiths, Marcus (2018) Identifying wheat root traits and regulatory genes for nitrogen uptake efficiency. PhD thesis, University of Nottingham.

Other

Atkinson, Jonathan A., Lobet, Guillaume, Noll, Manuel, Meyer, Patrick E., Griffiths, Marcus and Wells, Darren M. (2017) Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large scale genetic studies. bioRxiv, Cold Spring Harbor, N.Y., USA.

Pound, Michael P., Burgess, Alexandra J., Wilson, Michael H., Atkinson, Jonathan A., Griffiths, Marcus, Jackson, Aaron S., Bulat, Adrian, Tzimiropoulos, Yorgos, Wells, Darren M., Murchie, Erik H., Pridmore, Tony P. and French, Andrew P. (2016) Deep machine learning provides state-of-the art performance in image-based plant phenotyping. Cold Spring Harbor Laboratory.